The context of this study is to develop a methodology to evaluate the biogas surface emission from the anaerobic fermentation process linking with the waste landfill plants. The operators seek to valorize their emissions, and to reduce their leakage. The biogas is captured through a collection network installed on the core of non-dangerous solid waste sites, which works in depression to collect efficiently the biogas at its emission source. Solid wastes are considered as one of the principal source of greenhouse gas emission. The waste landfills are strongly monitored to supervise the valorization of the biogas and to limit the biogas emissions: it isn't possible to have a direct sampling of the biogas emission with available sensors (at the source, interface between ground and atmosphere). The evaluation of the emission of biogas is an important challenge for the regulation aspects and risk assessment. Consequently we develop an inverse method to estimate the flow (g/m2/s) using the monitoring of the CH4 air quality on the site The inverse approach uses a direct modeling of atmospheric dispersion (between source of emission and receptors) linked with an optimization approach to estimate the average flow of emission. Firstly the approach (method) was validated on simulated results on different scenarii (constant and fluctuant emissions) before being applied to real data. A second phase was dedicated to the evaluation of the uncertainty of the results. This inverse approach is already up and running with fair good results. However, the simulation study is quite time consuming. As consequence further works are going on to: - Reduce the dimension of the problem by using the correlations between the simulator's outputs - Model the inverse approach simulator by using a design of experiment based on kriging